Model
Model explorer

GPT-5.6 Luna

CLOSED
OpenAI · GPT-5.6 family · released Jul 9, 2026

Cheapest/fastest tier of the three-tier GPT-5.6 family (GA July 9, 2026 alongside Sol and Terra); OpenAI positions the tiers as 'durable capability tiers that can advance on their own cadence' — Luna targets cost-sensitive, high-volume workloads. Same 1.05M context, 128K max output and Feb 2026 knowledge cutoff as Sol. Price cut 80% on July 30, 2026 (launch $1/$6 → $0.20/$1.20 per MTok), taking it from a fifth to a twenty-fifth of Sol's price. Distinct model tier, not a reasoning-effort configuration of Sol (each tier separately exposes its own effort settings).

ReasoningCodingVisionFunction callingTool useAgentic
2534.3
Elo · rank #37
Parameters
Undisclosed
Active params
—
Context
1.05M tokens
Architecture
Undisclosed architecture (presumed dense transformer); fastest/cheapest 'durable capability tier' of the GPT-5.6 Sol/Terra/Luna family, built for cost-sensitive high-volume workloads
License
Proprietary
Languages
—
API price (in/out)
$0.2 / $1.2
Modalities
text · vision
Benchmark results
Bar shows position within the tracked field; marker = field best
Agents' Last ExamAgents50.3%#5
best: GPT-6 Astra · 59.3%
ARC-AGI-1Reasoning88.0%#17
best: Claude Fable 5 · 98.5%
ARC-AGI-2Reasoning59.5%#23
best: GPT-6 Astra · 95.0%
ARC-AGI-3Reasoning0.2%#10
best: GPT-6 Astra · 62.7%
Arena EloHuman preference1452#39
best: Claude Fable 5 · 1504
BrowseCompAgents83.3%#16
best: Kimi K3 · 91.2%
CyberGymCoding77.9%#10
best: MiMo-V2.6-Flash · 95.1%
FrontierBenchAgents14.3%#8
best: Claude Opus 5 · 43.3%
best: GPT-5.6 Sol · 89.0%
best: GPT-5.6 Sol · 83.0%
GDPval-AAAgents1591.8#15
best: Claude Fable 5 · 1932
GPQA DiamondReasoning92.3%#20
best: GPT-6 Astra · 96.0%
MMMU-ProVision78.4%#19
best: Claude Opus 4.7 · 85.5%
SWE-bench ProCoding62.7%#13
best: Claude Opus 5.5 · 89.9%
SWE-bench VerifiedCoding93.0%#8
best: Claude Opus 5 · 97.0%
τ³-BankingAgents27.2%#5
best: Step 5 Preview · 42.5%
Terminal-Bench 2.0Coding84.7%#13
best: DeepSeek-V4.1-Flash · 90.6%
Run it locally
Closed weights — available via API only. No local deployment.
Input / M tok
$0.2
Output / M tok
$1.2
API price $0.2/$1.2 · each benchmark row carries its own source badge (see methodology)